A large, multinational organization is about to undertake an ambitious transformation effort. To do this, it hires a seasoned chief transformation officer, who promptly sets up a project management office and begins to roll out detailed plans, carefully defined milestones, and a battery of Gantt charts.
While this is a common scene across corporate transformation programs, our research shows that only about 25% of such efforts succeed in both the short and long terms. Given this unimpressive track record, why do we keep relying on the same traditional change management tactics time after time?
Changing Change Management
Part of the problem is that the presumed supremacy of classical change management techniques blinds leaders to the variety of organizational contexts in which change occurs. Leaders therefore tend to rely on those standard approaches, rather than adapting their change strategy to their specific situation. Effective change management requires leaders to shift away from one-size-fits-all approaches and develop an expanded set of context-specific strategies.
An effective change strategy begins with an understanding of the specific mechanisms of change, as determined by the change context. We define a change context as the pattern of endogenous factors that shape how change spreads. Though change contexts can vary widely across organizations, leaders can benefit from recognizing a few salient archetypes from which more nuanced strategies can be constructed.
This article focuses on four key context archetypes. Simple change contexts are those in which agents are homogenous, predictable, and manageable. Unpredictable change contexts are those in which the relationships between inputs and outputs are unclear, so the effects of specific interventions are hard to predict. Interdependent contexts are those characterized by networks of reciprocal interactions in which social influence from peers has a stronger effect on agents’ behaviors than top-down influence. Finally, complicated contexts are those that are dynamic, large in scale, and/or composed of heterogenous agents. These archetypes do not exhaust the variety of possible change contexts. However, they highlight some ways in which change efforts need to depart from traditional change management techniques to be effective in specific contexts.
Each of these archetypes is associated with a characteristic family of interventions that can spread change within a given context. While traditional change management techniques work well in simple change contexts, they are less effective in unpredictable, interdependent, and complicated environments. To illustrate this idea, we have designed a change simulator that generates organizational networks to embody these different change contexts and models how they respond to various interventions.
As traditional sources of competitive advantage decline in persistence, increasing the speed at which leading companies are overtaken by competitors that operate on different business models, effective change management will become increasingly critical to success—and even survival. Therefore, instead of defaulting to the standard change management methods, leaders should adopt appropriate strategies of change that respond to the specific characteristics of the change context and adjust as the organization evolves.
Our proposed framework—which pairs context archetypes with appropriate interventions under holistic change philosophies—together with the change simulator, can help managers navigate a wider range of options to transform the organizations they lead.
Understanding Change Contexts
Depending on the intended change effort, a change context may encompass the entire organization or only a part, such as a single team. In either case, leaders need to understand how that context works—what drives agents’ current behaviors and what would be needed to change them. Leaders can do this by assessing individual change contexts against one of the four change context archetypes.
Simple contexts are those in which agents and activities are directlymanageable. Such contexts are characterized by relatively homogenous agents, interventions that have predictable outcomes, manageable scale, and agents that are responsive to top-down influence. These are contexts in which traditional change management works well and should be deployed. But leaders will often encounter contexts that depart from this simple archetype.
Unpredictable contexts are those in which leaders cannot predict the outcomes of interventions. For example, imagine that Company A wants to increase its rate of product innovation. However, it cannot simply mandate that employees submit new or better ideas because leaders would not be able to predict which employees would respond to the directive or how the types and styles of employee submissions might differ. Employee responses depend primarily on the employees’ interests and capabilities and are, therefore, difficult to anticipate.
Because outcomes in this context are unpredictable and their odds are unknown—and thus difficult to manage directly—change can most effectively be shaped by systematizing learning across the organization. To do this, leaders can create statistical learning systems that encourage experimentation, aggregate learnings, and iteratively adapt approaches to bring about the desired change.
Interdependent contexts are those in which peer influence is stronger than top-down directives. This is true when agents are connected through robust and reciprocal social networks, resulting in horizontal influence that is stronger than the effect of top-down mandates.
Suppose Company B is having trouble getting employees to buy into its new ethical AI policies, which encourage people to report any potential harms or risks associated with their projects—such as applying AI software to determine hiring criteria. Rather than following company-wide guidelines, individuals may tend to report concerns only if other people to whom they are socially connected do so as well. This behavior makes sense if people are more personally invested in the perceptions of members of their social groups—especially those with whom they interact frequently—than in the interests of company leadership.
In an interdependent context, change spreads primarily through reciprocal agent influence. Leaders can therefore spread change through “strategic activism”—the use of peer influence, interpersonal interventions, and incentives to amplify beneficial behaviors.
In complicated contexts, activities or agents are large in scale, heterogenous, and/or dynamic. These factors make direct management difficult even when outcomes are predictable and leadership retains a strong influence.
Imagine that Company C, a large, multinational organization, is just returning to the office following the COVID-19 pandemic. To avoid outbreaks across its various offices and regions, leaders want to increase employee vaccination rates. However, accomplishing this goal involves navigating the ever-changing nature of the pandemic, understanding numerous regional and local COVID regulations and vaccine availabilities, and addressing diverse—and potentially contradictory—employee opinions related to vaccine compliance. A one-size-fits-all, top-down solution will likely not work.
When facing a complicated change context, leaders can seek to transform it into a simpler one by, for instance, implementing mandates that standardize behavior or dividing the organization into smaller units. Furthermore, by using exploratory probes, tests, and pilots, leaders can learn how to reduce the influence of complicating factors.
Read the full article at https://www.bcg.com/en-mx/publications/2022/change-strategies-for-your-organization.